Properties of plant food allergens: In silico studies

International Comparative Medicine Symposium. Allergology. Revisión de métodos computacionales para determinar propiedades de alergenos alimentarios de plantas

Down-Regulating γ-gliadins in bread wheat leads to non-specific increases in other gluten proteins and has no major effect on dough gluten strength.

Background Gliadins are a major component of gluten proteins but their role in the mixing of dough is not well understood because their contribution to wheat flour functional properties are not as clear as for the glutenin fraction. Methodology/Principal Findings Transgenic lines of bread wheat with γ-gliadins suppressed by RNAi are reported. The effects on the gluten protein composition and on technological properties of flour were analyzed by RP-HPLC, by sodium dodecyl sulfate sedimentation (SDSS) test and by Mixograph analysis. The silencing of γ-gliadins by RNAi in wheat lines results in an increase in content of all other gluten proteins. Despite the gluten proteins compensation, in silico analysis of amino acid content showed no difference in the γ-gliadins silenced lines. The SDSS test and Mixograph parameters were slightly affected by the suppression of γ-gliadins. Conclusions/Significance Therefore, it is concluded that γ-gliadins do not have an essential functional contribution to the bread-making quality of wheat dough, and their role can be replaced by other gluten proteins

Mining Abstractions in Scientific Workows

Los flujos de trabajo científicos han sido adoptados durante la última década para representar los métodos computacionales utilizados en experimentos in silico, así como para dar soporte a sus publicaciones asociadas. Dichos flujos de trabajo han demostrado ser útiles para compartir y reproducir experimentos científicos, permitiendo a investigadores visualizar, depurar y ahorrar tiempo a la hora de re-ejecutar un trabajo realizado con anterioridad. Sin embargo, los flujos de trabajo científicos pueden ser en ocasiones difíciles de entender y reutilizar. Esto es debido a impedimentos como el gran número de flujos de trabajo existentes en repositorios, su heterogeneidad o la falta generalizada de documentación y ejemplos de uso. Además, dado que normalmente es posible implementar un mismo método utilizando algoritmos o técnicas distintas, flujos de trabajo aparentemente distintos pueden estar relacionados a un determinado nivel de abstracción, basándose, por ejemplo, en su funcionalidad común. Esta tesis se centra en la reutilización de flujos de trabajo y su abstracción mediante la exploración de relaciones entre los flujos de trabajo de un repositorio y la extracción de abstracciones que podrían ayudar a la hora de reutilizar otros flujos de trabajo existentes. Para ello, se propone un modelo simple de representación de flujos de trabajo y sus ejecuciones, se analizan las abstracciones típicas que se pueden encontrar en los repositorios de flujos de trabajo, se exploran las prácticas habituales de los usuarios a la hora de reutilizar flujos de trabajo existentes y se describe un método para descubrir abstracciones útiles para usuarios, basadas en técnicas existentes de teoría de grafos. Los resultados obtenidos exponen las abstracciones y prácticas comunes de usuarios en términos de reutilización de flujos de trabajo, y muestran cómo las abstracciones que se extraen automáticamente tienen potencial para ser reutilizadas por usuarios que buscan diseñar nuevos flujos de trabajo. Abstract Scientific workflows have been adopted in the last decade to represent the computational methods used in in silico scientific experiments and their associated research products. Scientific workflows have demonstrated to be useful for sharing and reproducing scientific experiments, allowing scientists to visualize, debug and save time when re-executing previous work. However, scientific workflows may be difficult to understand and reuse. The large amount of available workflows in repositories, together with their heterogeneity and lack of documentation and usage examples may become an obstacle for a scientist aiming to reuse the work from other scientists. Furthermore, given that it is often possible to implement a method using different algorithms or techniques, seemingly disparate workflows may be related at a higher level of abstraction, based on their common functionality. In this thesis we address the issue of reusability and abstraction by exploring how workflows relate to one another in a workflow repository, mining abstractions that may be helpful for workflow reuse. In order to do so, we propose a simple model for representing and relating workflows and their executions, we analyze the typical common abstractions that can be found in workflow repositories, we explore the current practices of users regarding workflow reuse and we describe a method for discovering useful abstractions for workflows based on existing graph mining techniques. Our results expose the common abstractions and practices of users in terms of workflow reuse, and show how our proposed abstractions have potential to become useful for users designing new workflows.

Proposal of a trust and reputation model to provide recommendation in open quality oriented environments

El auge y penetración de las nuevas tecnologías junto con la llamada Web Social están cambiando la forma en la que accedemos a la medicina. Cada vez más pacientes y profesionales de la medicina están creando y consumiendo recursos digitales de contenido clínico a través de Internet, surgiendo el problema de cómo asegurar la fiabilidad de estos recursos. Además, un nuevo concepto está apareciendo, el de pervasive healthcare o sanidad ubicua, motivado por pacientes que demandan un acceso a los servicios sanitarios en todo momento y en todo lugar. Este nuevo escenario lleva aparejado un problema de confianza en los proveedores de servicios sanitarios. Las plataformas de eLearning se están erigiendo como paradigma de esta nueva Medicina 2.0 ya que proveen un servicio abierto a la vez que controlado/supervisado a recursos digitales, y facilitan las interacciones y consultas entre usuarios, suponiendo una buena aproximación para esta sanidad ubicua. En estos entornos los problemas de fiabilidad y confianza pueden ser solventados mediante la implementación de mecanismos de recomendación de recursos y personas de manera confiable. Tradicionalmente las plataformas de eLearning ya cuentan con mecanismos de recomendación, si bien están más enfocados a la recomendación de recursos. Para la recomendación de usuarios es necesario acudir a mecanismos más elaborados como son los sistemas de confianza y reputación (trust and reputation) En ambos casos, tanto la recomendación de recursos como el cálculo de la reputación de los usuarios se realiza teniendo en cuenta criterios principalmente subjetivos como son las opiniones de los usuarios. En esta tesis doctoral proponemos un nuevo modelo de confianza y reputación que combina evaluaciones automáticas de los recursos digitales en una plataforma de eLearning, con las opiniones vertidas por los usuarios como resultado de las interacciones con otros usuarios o después de consumir un recurso. El enfoque seguido presenta la novedad de la combinación de una parte objetiva con otra subjetiva, persiguiendo mitigar el efecto de posibles castigos subjetivos por parte de usuarios malintencionados, a la vez que enriquecer las evaluaciones objetivas con información adicional acerca de la capacidad pedagógica del recurso o de la persona. El resultado son recomendaciones siempre adaptadas a los requisitos de los usuarios, y de la máxima calidad tanto técnica como educativa. Esta nueva aproximación requiere una nueva herramienta para su validación in-silico, al no existir ninguna aplicación que permita la simulación de plataformas de eLearning con mecanismos de recomendación de recursos y personas, donde además los recursos sean evaluados objetivamente. Este trabajo de investigación propone pues una nueva herramienta, basada en el paradigma de programación orientada a agentes inteligentes para el modelado de comportamientos complejos de usuarios en plataformas de eLearning. Además, la herramienta permite también la simulación del funcionamiento de este tipo de entornos dedicados al intercambio de conocimiento. La evaluación del trabajo propuesto en este documento de tesis se ha realizado de manera iterativa a lo largo de diferentes escenarios en los que se ha situado al sistema frente a una amplia gama de comportamientos de usuarios. Se ha comparado el rendimiento del modelo de confianza y reputación propuesto frente a dos modos de recomendación tradicionales: a) utilizando sólo las opiniones subjetivas de los usuarios para el cálculo de la reputación y por extensión la recomendación; y b) teniendo en cuenta sólo la calidad objetiva del recurso sin hacer ningún cálculo de reputación. Los resultados obtenidos nos permiten afirmar que el modelo desarrollado mejora la recomendación ofrecida por las aproximaciones tradicionales, mostrando una mayor flexibilidad y capacidad de adaptación a diferentes situaciones. Además, el modelo propuesto es capaz de asegurar la recomendación de nuevos usuarios entrando al sistema frente a la nula recomendación para estos usuarios presentada por el modo de recomendación predominante en otras plataformas que basan la recomendación sólo en las opiniones de otros usuarios. Por último, el paradigma de agentes inteligentes ha probado su valía a la hora de modelar plataformas virtuales complejas orientadas al intercambio de conocimiento, especialmente a la hora de modelar y simular el comportamiento de los usuarios de estos entornos. La herramienta de simulación desarrollada ha permitido la evaluación del modelo de confianza y reputación propuesto en esta tesis en una amplia gama de situaciones diferentes. ABSTRACT Internet is changing everything, and this revolution is especially present in traditionally offline spaces such as medicine. In recent years health consumers and health service providers are actively creating and consuming Web contents stimulated by the emergence of the Social Web. Reliability stands out as the main concern when accessing the overwhelming amount of information available online. Along with this new way of accessing the medicine, new concepts like ubiquitous or pervasive healthcare are appearing. Trustworthiness assessment is gaining relevance: open health provisioning systems require mechanisms that help evaluating individuals’ reputation in pursuit of introducing safety to these open and dynamic environments. Technical Enhanced Learning (TEL) -commonly known as eLearning- platforms arise as a paradigm of this Medicine 2.0. They provide an open while controlled/supervised access to resources generated and shared by users, enhancing what it is being called informal learning. TEL systems also facilitate direct interactions amongst users for consultation, resulting in a good approach to ubiquitous healthcare. The aforementioned reliability and trustworthiness problems can be faced by the implementation of mechanisms for the trusted recommendation of both resources and healthcare services providers. Traditionally, eLearning platforms already integrate recommendation mechanisms, although this recommendations are basically focused on providing an ordered classifications of resources. For users’ recommendation, the implementation of trust and reputation systems appears as the best solution. Nevertheless, both approaches base the recommendation on the information from the subjective opinions of other users of the platform regarding the resources or the users. In this PhD work a novel approach is presented for the recommendation of both resources and users within open environments focused on knowledge exchange, as it is the case of TEL systems for ubiquitous healthcare. The proposed solution adds the objective evaluation of the resources to the traditional subjective personal opinions to estimate the reputation of the resources and of the users of the system. This combined measure, along with the reliability of that calculation, is used to provide trusted recommendations. The integration of opinions and evaluations, subjective and objective, allows the model to defend itself against misbehaviours. Furthermore, it also allows ‘colouring’ cold evaluation values by providing additional quality information such as the educational capacities of a digital resource in an eLearning system. As a result, the recommendations are always adapted to user requirements, and of the maximum technical and educational quality. To our knowledge, the combination of objective assessments and subjective opinions to provide recommendation has not been considered before in the literature. Therefore, for the evaluation of the trust and reputation model defined in this PhD thesis, a new simulation tool will be developed following the agent-oriented programming paradigm. The multi-agent approach allows an easy modelling of independent and proactive behaviours for the simulation of users of the system, conforming a faithful resemblance of real users of TEL platforms. For the evaluation of the proposed work, an iterative approach have been followed, testing the performance of the trust and reputation model while providing recommendation in a varied range of scenarios. A comparison with two traditional recommendation mechanisms was performed: a) using only users’ past opinions about a resource and/or other users; and b) not using any reputation assessment and providing the recommendation considering directly the objective quality of the resources. The results show that the developed model improves traditional approaches at providing recommendations in Technology Enhanced Learning (TEL) platforms, presenting a higher adaptability to different situations, whereas traditional approaches only have good results under favourable conditions. Furthermore the promotion period mechanism implemented successfully helps new users in the system to be recommended for direct interactions as well as the resources created by them. On the contrary OnlyOpinions fails completely and new users are never recommended, while traditional approaches only work partially. Finally, the agent-oriented programming (AOP) paradigm has proven its validity at modelling users’ behaviours in TEL platforms. Intelligent software agents’ characteristics matched the main requirements of the simulation tool. The proactivity, sociability and adaptability of the developed agents allowed reproducing real users’ actions and attitudes through the diverse situations defined in the evaluation framework. The result were independent users, accessing to different resources and communicating amongst them to fulfil their needs, basing these interactions on the recommendations provided by the reputation engine.

Detecting common scientific workflow fragments using templates and execution provenance

Provenance plays a major role when understanding and reusing the methods applied in a scientic experiment, as it provides a record of inputs, the processes carried out and the use and generation of intermediate and nal results. In the specic case of in-silico scientic experiments, a large variety of scientic workflow systems (e.g., Wings, Taverna, Galaxy, Vistrails) have been created to support scientists. All of these systems produce some sort of provenance about the executions of the workflows that encode scientic experiments. However, provenance is normally recorded at a very low level of detail, which complicates the understanding of what happened during execution. In this paper we propose an approach to automatically obtain abstractions from low-level provenance data by finding common workflow fragments on workflow execution provenance and relating them to templates. We have tested our approach with a dataset of workflows published by the Wings workflow system. Our results show that by using these kinds of abstractions we can highlight the most common abstract methods used in the executions of a repository, relating different runs and workflow templates with each other.

Propuesta de algoritmos de predicción de glucosa en pacientes diabéticos

La diabetes mellitus es el conjunto de alteraciones provocadas por un defecto en la cantidad de insulina secretada o por un aprovechamiento deficiente de la misma. Es causa directa de complicaciones a corto, medio y largo plazo que disminuyen la calidad y las expectativas de vida de las personas con diabetes. La diabetes mellitus es en la actualidad uno de los problemas más importantes de salud. Ha triplicado su prevalencia en los últimos 20 anos y para el año 2025 se espera que existan casi 300 millones de personas con diabetes. Este aumento de la prevalencia junto con la morbi-mortalidad asociada a sus complicaciones micro y macro-vasculares convierten la diabetes en una carga para los sistemas sanitarios, sus recursos económicos y sus profesionales, haciendo de la enfermedad un problema individual y de salud pública de enormes proporciones. De momento no existe cura a esta enfermedad, de modo que el objetivo terapéutico del tratamiento de la diabetes se centra en la normalización de la glucemia intentando minimizar los eventos de hiper e hipoglucemia y evitando la aparición o al menos retrasando la evolución de las complicaciones vasculares, que constituyen la principal causa de morbi-mortalidad de las personas con diabetes. Un adecuado control diabetológico implica un tratamiento individualizado que considere multitud de factores para cada paciente (edad, actividad física, hábitos alimentarios, presencia de complicaciones asociadas o no a la diabetes, factores culturales, etc.). Sin embargo, a corto plazo, las dos variables más influyentes que el paciente ha de manejar para intervenir sobre su nivel glucémico son la insulina administrada y la dieta. Ambas presentan un retardo entre el momento de su aplicación y el comienzo de su acción, asociado a la absorción de los mismos. Por este motivo la capacidad de predecir la evolución del perfil glucémico en un futuro cercano, ayudara al paciente a tomar las decisiones adecuadas para mantener un buen control de su enfermedad y evitar situaciones de riesgo. Este es el objetivo de la predicción en diabetes: adelantar la evolución del perfil glucémico en un futuro cercano para ayudar al paciente a adaptar su estilo de vida y sus acciones correctoras, con el propósito de que sus niveles de glucemia se aproximen a los de una persona sana, evitando así los síntomas y complicaciones de un mal control. La aparición reciente de los sistemas de monitorización continua de glucosa ha proporcionado nuevas alternativas. La disponibilidad de un registro exhaustivo de las variaciones del perfil glucémico, con un periodo de muestreo de entre uno y cinco minutos, ha favorecido el planteamiento de nuevos modelos que tratan de predecir la glucemia utilizando tan solo las medidas anteriores de glucemia o al menos reduciendo significativamente la información de entrada a los algoritmos. El hecho de requerir menor intervención por parte del paciente, abre nuevas posibilidades de aplicación de los predictores de glucemia, haciéndose viable su uso en tiempo real, como sistemas de ayuda a la decisión, como detectores de situaciones de riesgo o integrados en algoritmos automáticos de control. En esta tesis doctoral se proponen diferentes algoritmos de predicción de glucemia para pacientes con diabetes, basados en la información registrada por un sistema de monitorización continua de glucosa así como incorporando la información de la insulina administrada y la ingesta de carbohidratos. Los algoritmos propuestos han sido evaluados en simulación y utilizando datos de pacientes registrados en diferentes estudios clínicos. Para ello se ha desarrollado una amplia metodología, que trata de caracterizar las prestaciones de los modelos de predicción desde todos los puntos de vista: precisión, retardo, ruido y capacidad de detección de situaciones de riesgo. Se han desarrollado las herramientas de simulación necesarias y se han analizado y preparado las bases de datos de pacientes. También se ha probado uno de los algoritmos propuestos para comprobar la validez de la predicción en tiempo real en un escenario clínico. Se han desarrollado las herramientas que han permitido llevar a cabo el protocolo experimental definido, en el que el paciente consulta la predicción bajo demanda y tiene el control sobre las variables metabólicas. Este experimento ha permitido valorar el impacto sobre el control glucémico del uso de la predicción de glucosa. ABSTRACT Diabetes mellitus is the set of alterations caused by a defect in the amount of secreted insulin or a suboptimal use of insulin. It causes complications in the short, medium and long term that affect the quality of life and reduce the life expectancy of people with diabetes. Diabetes mellitus is currently one of the most important health problems. Prevalence has tripled in the past 20 years and estimations point out that it will affect almost 300 million people by 2025. Due to this increased prevalence, as well as to morbidity and mortality associated with micro- and macrovascular complications, diabetes has become a burden on health systems, their financial resources and their professionals, thus making the disease a major individual and a public health problem. There is currently no cure for this disease, so that the therapeutic goal of diabetes treatment focuses on normalizing blood glucose events. The aim is to minimize hyper- and hypoglycemia and to avoid, or at least to delay, the appearance and development of vascular complications, which are the main cause of morbidity and mortality among people with diabetes. A suitable, individualized and controlled treatment for diabetes involves many factors that need to be considered for each patient: age, physical activity, eating habits, presence of complications related or unrelated to diabetes, cultural factors, etc. However, in the short term, the two most influential variables that the patient has available in order to manage his/her glycemic levels are administered insulin doses and diet. Both suffer from a delay between their time of application and the onset of the action associated with their absorption. Therefore, the ability to predict the evolution of the glycemic profile in the near future could help the patient to make appropriate decisions on how to maintain good control of his/her disease and to avoid risky situations. Hence, the main goal of glucose prediction in diabetes consists of advancing the evolution of glycemic profiles in the near future. This would assist the patient in adapting his/her lifestyle and in taking corrective actions in a way that blood glucose levels approach those of a healthy person, consequently avoiding the symptoms and complications of a poor glucose control. The recent emergence of continuous glucose monitoring systems has provided new alternatives in this field. The availability of continuous records of changes in glycemic profiles (with a sampling period of one or five minutes) has enabled the design of new models which seek to predict blood glucose by using automatically read glucose measurements only (or at least, reducing significantly the data input manually to the algorithms). By requiring less intervention by the patient, new possibilities are open for the application of glucose predictors, making its use feasible in real-time applications, such as: decision support systems, hypo- and hyperglycemia detectors, integration into automated control algorithms, etc. In this thesis, different glucose prediction algorithms are proposed for patients with diabetes. These are based on information recorded by a continuous glucose monitoring system and incorporate information of the administered insulin and carbohydrate intakes. The proposed algorithms have been evaluated in-silico and using patients’ data recorded in different clinical trials. A complete methodology has been developed to characterize the performance of predictive models from all points of view: accuracy, delay, noise and ability to detect hypo- and hyperglycemia. In addition, simulation tools and patient databases have been deployed. One of the proposed algorithms has additionally been evaluated in terms of real-time prediction performance in a clinical scenario in which the patient checked his/her glucose predictions on demand and he/she had control on his/her metabolic variables. This has allowed assessing the impact of using glucose prediction on glycemic control. The tools to carry out the defined experimental protocols were also developed in this thesis.

Modeling iron-catecholates binding to NGAL protein

Neutrophil gelatinase associated lipocalin (NGAL) protein is attracting a great interest because of its antibacterial properties played upon modulating iron content in competition against iron acquisition processes developed by pathogenic bacteria that bind selective ferric iron chelators (siderophores). Besides its known high affinity to enterobactin, the most important siderophore, it has been recently shown that NGAL is able to bind Fe(III) coordinated by catechols. The selective binding of Fe(III)-catechol ligands to NGAL is here studied by using iron coordination structures with one, two, and three catecholate ligands. By means of a computational approach that consists of B3LYP/6-311G(d,p) quantum calculations for geometries, electron properties and electrostatic potentials of ligands, protein–ligand flexible docking calculations, analyses of protein–ligand interfaces, and Poisson–Boltzmann electrostatic potentials for proteins, we study the binding of iron catecholate ligands to NGAL as a central member of the lipocalin family of proteins. This approach provides a modeling basis for exploring in silico the selective binding of iron catecholates ligands giving a detailed picture of their interactions in terms of electrostatic effects and a network of hydrogen bonds in the protein binding pocket.

Factores transcripcionales de la clase DOF en Brachypodium distachyon: caracterización molecular de BdDOF24 durante la germinación de las semillas

La semilla es el órgano que garantiza la propagación y continuidad evolutiva de las plantas espermatofitas y constituye un elemento indispensable en la alimentación humana y animal. La semilla de cereales acumula en el endospermo durante la maduración, mayoritariamente, almidón y proteínas de reserva. Estas reservas son hidrolizadas en la germinación por hidrolasas sintetizadas en la aleurona en respuesta a giberelinas (GA), siendo la principal fuente de energía hasta que la plántula emergente es fotosintéticamente activa. Ambas fases del desarrollo de la semilla, están reguladas por una red de factores de transcripción (TF) que unen motivos conservados en cis- en los promotores de sus genes diana. Los TFs son proteínas que han desempeñado un papel central en la evolución y en el proceso de domesticación, siendo uno de los principales mecanismos de regulación génica; en torno al 7% de los genes de plantas codifican TFs. Atendiendo al motivo de unión a DNA, éstos, se han clasificado en familias. La familia DOF (DNA binding with One Finger) participa en procesos vitales exclusivos de plantas superiores y sus ancestros cercanos (algas, musgos y helechos). En las semillas de las Triticeae (subfamilia Pooideae), se han identificado varias proteínas DOF que desempeñan un papel fundamental en la regulación de la expresión génica. Brachypodium distachyon es la primera especie de la subfamilia Pooideae cuyo genoma (272 Mbp) ha sido secuenciado. Su pequeño tamaño, ciclo de vida corto, y la posibilidad de ser transformado por Agrobacterium tumefaciens (plásmido Ti), hacen que sea el sistema modelo para el estudio de cereales de la tribu Triticeae con gran importancia agronómica mundial, como son el trigo y la cebada. En este trabajo, se han identificado 27 genes Dof en el genoma de B. distachyon y se han establecido las relaciones evolutivas entre estos genes Dof y los de cebada (subfamilia Pooideae) y de arroz (subfamilia Oryzoideae), construyendo un árbol filogenético en base al alineamiento múltiple del dominio DOF. La cebada contiene 26 genes Dof y en arroz se han anotado 30. El análisis filogenético establece cuatro grupos de genes ortólogos (MCOGs: Major Clusters of Orthologous Genes), que están validados por motivos conservados adicionales, además del dominio DOF, entre las secuencias de las proteínas de un mismo MCOG. El estudio global de expresión en diferentes órganos establece un grupo de nueve genes BdDof expresados abundantemente y/o preferencialmente en semillas. El estudio detallado de expresión de estos genes durante la maduración y germinación muestra que BdDof24, ortólogo putativo a BPBF-HvDOF24 de cebada, es el gen más abundante en las semillas en germinación de B. distachyon. La regulación transcripcional de los genes que codifican hidrolasas en la aleurona de las semillas de cereales durante la post‐germinación ha puesto de manifiesto la existencia en sus promotores de un motivo tripartito en cis- conservado GARC (GA-Responsive Complex), que unen TFs de la clase MYB-R2R3, DOF y MYBR1-SHAQKYF. En esta tesis, se ha caracterizado el gen BdCathB de Brachypodium que codifica una proteasa tipo catepsina B y es ortólogo a los genes Al21 de trigo y HvCathB de cebada, así como los TFs responsables de su regulación transcripcional BdDOF24 y BdGAMYB (ortólogo a HvGAMYB). El análisis in silico del promotor BdCathB ha identificado un motivo GARC conservado, en posición y secuencia, con sus ortólogos en trigo y cebada. La expresión de BdCathB se induce durante la germinación, así como la de los genes BdDof24 y BdGamyb. Además, los TFs BdDOF24 y BdGAMYB interaccionan en el sistema de dos híbridos de levadura e in planta en experimentos de complementación bimolecular fluorescente. En capas de aleurona de cebada, BdGAMYB activa el promotor BdCathB, mientras que BdDOF24 lo reprime; este resultado es similar al obtenido con los TFs ortólogos de cebada BPBF-HvDOF24 y HvGAMYB. Sin embargo, cuando las células de aleurona se transforman simultáneamente con los dos TFs, BdDOF24 tiene un efecto aditivo sobre la trans-activación mediada por BdGAMYB, mientras que su ortólogo BPBF-HvDOF24 produce el efecto contrario, revirtiendo el efecto de HvGAMYB sobre el promotor BdCathB. Las diferencias entre las secuencias deducidas de las proteínas BdDOF24 y BPBF-HvDOF24 podrían explicar las funciones opuestas que desempeñan en su interacción con GAMYB. Resultados preliminares con líneas de inserción de T-DNA y de sobre-expresión estable de BdGamyb, apoyan los resultados obtenidos en expresión transitoria. Además las líneas homocigotas knock-out para el gen BdGamyb presentan alteraciones en anteras y polen y no producen semillas viables. ABSTRACT The seed is the plant organ of the spermatophytes responsible for the dispersion and survival in the course of evolution. In addition, it constitutes one of the most importan elements of human food and animal feed. The main reserves accumulated in the endosperm of cereal seeds through the maturation phase of development are starch and proteins. Its degradation by hydrolases synthetized in aleurone cells in response to GA upon germination provides energy, carbon and nitrogen to the emerging seedling before it acquires complete photosynthetic capacity. Both phases of seed development are controlled by a network of transcription factors (TFs) that interact with specific cis- elements in the promoters of their target genes. TFs are proteins that have played a central role during evolution and domestication, being one of the most important regulatory mechanisms of gene expression. Around 7% of genes in plant genomes encode TFs. Based on the DNA binding motif, TFs are classified into families. The DOF (DNA binding with One Finger) family is involved in specific processes of plants and its ancestors (algae, mosses and ferns). Several DOF proteins have been described to play important roles in the regulation of genes in seeds of the Triticeae tribe (Pooideae subfamily). Brachypodium distachyon is the first member of the Pooideae subfamily to be sequenced. Its small size and compact structured genome (272 Mbp), the short life cycle, small plant size and the possibility of being transformed with Agrobacterium tumefaciens (Ti-plasmid) make Brachypodium the model system for comparative studies within cereals of the Triticeae tribe that have big economic value such as wheat and barley. In this study, 27 Dof genes have been identified in the genome of B. distachyon and the evolutionary relationships among these Dof genes and those frome barley (Pooideae subfamily) and those from rice (Oryzoideae subfamily) have been established by building a phylogenetic tree based on the multiple alignment of the DOF DNA binding domains. The barley genome (Hordeum vulgare) contains 26 Dof genes and in rice (Oryza sativa) 30 genes have been annotated. The phylogenetic analysis establishes four Major Clusters of Orthologous Genes (MCOGs) that are supported by additional conserved motives out of the DOF domain, between proteins of the same MCOG. The global expression study of BdDof genes in different organs and tissues classifies BdDof genes into two groups; nine of the 27 BdDof genes are abundantly or preferentially expressed in seeds. A more detailed expression analysis of these genes during seed maturation and germination shows that BdDof24, orholog to barley BPBF-HvDof24, is the most abundantly expressed gene in germinating seeds. Transcriptional regulation studies of genes that encode hydrolases in aleurone cells during post-germination of cereal seeds, have identified in their promoters a tripartite conserved cis- motif GARC (GA-Responsive Complex) that binds TFs of the MYB-R2R3, DOF and MYBR1-SHAQKYF families. In this thesis, the characterization of the BdCathB gene, encoding a Cathepsin B-like protease and that is ortholog to the wheat Al21 and the barley HvCathB genes, has been done and its transcriptional regulation by the TFs BdDOF24 and BdGAMYB (ortholog to HvGAMYB) studied. The in silico analysis of the BdCathB promoter sequence has identified a GARC motif. BdCathB expression is induced upon germination, as well as, those of BdDof24 and BdGamyb genes. Moreover, BdDOF24 and BdGAMYB interact in yeast (Yeast 2 Hybrid System, Y2HS) and in planta (Bimolecular Fluorecence Complementation, BiFC). In transient assays in aleurone cells, BdGAMYB activates the BdCathB promoter, whereas BdDOF24 is a transcriptional repressor, this result is similar to that obtained with the barley orthologous genes BPBF-HvDOF24 and HvGAMYB. However, when aleurone cells are simultaneously transformed with both TFs, BdDOF24 has an additive effect to the trans-activation mediated by BdGAMYB, while its ortholog BPBF-HvDOF24 produces an opposite effect by reducing the HvGAMYB activation of the BdCathB promoter. The differences among the deduced protein sequences between BdDOF24 and BPBF-HvDOF24 could explain their opposite functions in the interaction with GAMYB protein. Preliminary results of T-DNA insertion (K.O.) and stable over-expression lines of BdGamyb support the data obtained in transient expression assays. In addition, the BdGamyb homozygous T-DNA insertion (K.O.) lines have anther and pollen alterations and they do not produce viable seeds.

Identificación y análisis funcional de genes implicados en la homeostasis de níquel en la bacteria endosimbiótica de leguminosas Rhizobium leguminosarum

La asociación Rhizobium-leguminosa constituye una interacción planta-microorganismo particularmente beneficiosa a nivel medioambiental debido a su capacidad promotora del crecimiento vegetal en condiciones de deficiencia de nitrógeno. Se ha demostrado que una excesiva concentración de metales pesados en el suelo afecta negativamente la competitividad bacteriana y al desarrollo de interacciones diazotróficas eficientes (Chaudri et al., 2000; Pereira et al., 2006). Por otro lado, el suministro de metales como Fe, Mo, Ni o Cu es fundamental para la biosíntesis de enzimas bacterianas relacionadas con el proceso de fijación de nitrógeno que ocurre en el interior de los nódulos de las leguminosas (Moreau et al., 1995). Con objeto de identificar sistemas génicos implicados en la homeostasis de níquel en bacterias endosimbióticas, se ha llevado a cabo una mutagénesis mediante inserción aleatoria de un minitransposón derivado de Tn5 en Rhizobium leguminosarum bv. viciae UPM1137, una cepa capaz de resistir elevadas concentraciones de níquel y cobalto. Como resultado de esta mutagénesis se han obtenido 14 mutantes incapaces de crecer en medios suplementados con NiCl2. La localización de la inserción en estos mutantes muestra que una elevada proporción de los genes afectados codifican proteínas de membrana o proteínas secretadas. En paralelo, se ha obtenido la secuencia del genoma de la cepa UPM1137, lo que permite realizar estudios in silico comparando los genomas disponibles de varias cepas de R. leguminosarum bv. viciae, que presentan una menor sensibilidad a metales. El análisis bioinformático de los genomas secuenciados y la caracterización fenotípica de los mutantes obtenidos permitirá identificar potenciales sistemas de resistencia y su contribución a la homeostasis de metales.

Molecular tools to improve chestnut management: El Bierzo as a case study

The European chestnut (Castanea sativa Mill.) is a multipurpose species that has been widely cultivated around the Mediterranean basin since ancient times. New varieties were brought to the Iberian Peninsula during the Roman Empire, which coexist since then with native populations that survived the last glaciation. The relevance of chestnut cultivation has being steadily growing since the Middle Ages, until the rural decline of the past century put a stop to this trend. Forest fires and diseases were also major factors. Chestnut cultivation is gaining momentum again due to its economic (wood, fruits) and ecologic relevance, and represents currently an important asset in many rural areas of Europe. In this Thesis we apply different molecular tools to help improve current management strategies. For this study we have chosen El Bierzo (Castile and Leon, NW Spain), which has a centenary tradition of chestnut cultivation and management, and also presents several unique features from a genetic perspective (next paragraph). Moreover, its nuts are widely appreciated in Spain and abroad for their organoleptic properties. We have focused our experimental work on two major problems faced by breeders and the industry: the lack of a fine-grained genetic characterization and the need for new strategies to control blight disease. To characterize with sufficient detail the genetic diversity and structure of El Bierzo orchards, we analyzed DNA from 169 trees grafted for nut production covering the entire region. We also analyzed 62 nuts from all traditional varieties. El Bierzo constitutes an outstanding scenario to study chestnut genetics and the influence of human management because: (i) it is located at one extreme of the distribution area; (ii) it is a major glacial refuge for the native species; (iii) it has a long tradition of human management (since Roman times, at least); and (iv) its geographical setting ensures an unusual degree of genetic isolation. Thirteen microsatellite markers provided enough informativeness and discrimination power to genotype at the individual level. Together with an unexpected level of genetic variability, we found evidence of genetic structure, with three major gene pools giving rise to the current population. High levels of genetic differentiation between groups supported this organization. Interestingly, genetic structure does not match with spatial boundaries, suggesting that the exchange of material and cultivation practices have strongly influenced natural gene flow. The microsatellite markers selected for this study were also used to classify a set of 62 samples belonging to all traditional varieties. We identified several cases of synonymies and homonymies, evidencing the need to substitute traditional classification systems with new tools for genetic profiling. Management and conservation strategies should also benefit from these tools. The avenue of high-throughput sequencing technologies, combined with the development of bioinformatics tools, have paved the way to study transcriptomes without the need for a reference genome. We took advantage of RNA sequencing and de novo assembly tools to determine the transcriptional landscape of chestnut in response to blight disease. In addition, we have selected a set of candidate genes with high potential for developing resistant varieties via genetic engineering. Our results evidenced a deep transcriptional reprogramming upon fungal infection. The plant hormones ET and JA appear to orchestrate the defensive response. Interestingly, our results also suggest a role for auxins in modulating such response. Many transcription factors were identified in this work that interact with promoters of genes involved in disease resistance. Among these genes, we have conducted a functional characterization of a two major thaumatin-like proteins (TLP) that belongs to the PR5 family. Two genes encoding chestnut cotyledon TLPs have been previously characterized, termed CsTL1 and CsTL2. We substantiate here their protective role against blight disease for the first time, including in silico, in vitro and in vivo evidence. The synergy between TLPs and other antifungal proteins, particularly endo-p-1,3-glucanases, bolsters their interest for future control strategies based on biotechnological approaches.

Glucose-Insulin regulator for type 1 diabetes using high order neural networks

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period.